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Channel

MLSecOps | AI Governance | AI Reliability & Safety | IT Trends

@ml_ops

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

1,256subscribers

+1 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002327624890
TypeChannel
Username@ml_ops
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 11 August 2026
On Telegramt.me/ml_ops

Growth

1,2551,2561,255.57 August 2026 — 1,255 subscribers7 August 2026 — 1,255 subscribers11 August 2026 — 1,256 subscribers7 August 202611 August 2026
3 measurements spanning 4 days, net +1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 1,255–1,256 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 11:341,256+1
7 Aug 2026, 22:481,255no change
7 Aug 2026, 17:301,255first reading

Engagement

20 posts held, back to 10 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
16.3%
avg views ÷ 1,256 subscribers
Avg views / post
204
17 posts measured
Reaction rate
1.67%
reactions ÷ views · ER floor
Posts in window
17
of 20 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held20 (10 July 20267 August 2026)
Views total3,471
Reactions total58
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 22:48 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

68 reactions across 20 posts, in 7 distinct kinds. The most used accounts for 63.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥4363.2%
😱1623.5%
34.41%
22.94%
👍22.94%
😢11.47%
🤗11.47%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 20 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 68reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 10 July 2026 to 7 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

7 Aug 2026, 15:01 UTC78 views3 reactionsread 7 August 2026

ИИ-модель Qwen3.8-Max - очередной прорыв Китая, бросающий вызов американским конкурентам, — Bloomberg Китайская Alibaba выпустила свою самую мощную модель искусственного интеллекта (ИИ) Qwen3.8-Max, основанную на 2,4 трлн параметров. Новая модель показывает сопоставимые, а иногда и лучшие результаты, чем американская Fable 5 от Anthropic (передовая американская ИИ-модель, которая помещена под экспортный контроль в

🔥3

5 Aug 2026, 14:47 UTC75 views3 reactionsread 7 August 2026
Forwarded from @kokuykinPhoto

OWASP выпустил новую версию Top 10 for LLM Applications 2026. 1. Prompt Injection 2. Sensitive Information Disclosure 3. Excessive Agency 4. Supply Chain 5. Data and Model Poisoning 6. Unbounded Consumption 7. Misinformation 8. Hidden Context Exposure 9. Vector and Embedding Weaknesses 10. Improper Output Handling Как и другие гайды проекта, этот список формировался силами сообщества. Участники предлагали новые кат

🔥3

5 Aug 2026, 12:25 UTC97 views4 reactionsread 7 August 2026

Федеральный закон от 26 июля 2026 г. № 243-ФЗ "О поддержке развития технологий искусственного интеллекта в Российской Федерации" Дата подписания: 26.07.2026 Опубликован: 31.07.2026 Вступает в силу: 01.09.2026, 01.03.2027 Привет, мои дорогие и самые талантливые друзья! Сегодня сделаем обзор нового российского ФЗ в сфере ИИ (как и говорил всегда, нормативки по ИИ теперь будет много, и она будет расти по экспоненте).

🔥4

5 Aug 2026, 12:25 UTC114 views4 reactionsread 7 August 2026

5. Новое регулирование будет зависеть от того, какой вред может нанести ИИ. При этом одним из базовых принципов закона является «учет и уважение традиционных российских духовно-нравственных ценностей». Это означает, что на этапе государственной сертификации модели будут проверять не только на кибербезопасность, но и на «политкорректность» с точки зрения государственной идеологии (патриотизм, историческая память, прио

🔥4

5 Aug 2026, 12:00 UTC112 views2 reactionsread 7 August 2026

Еврокомиссия сможет ограничивать доступ к рынку, требовать проверки моделей и штрафовать разработчиков на сумму до 15 млн евро или 3% годового оборота Европейская комиссия получила новые полномочия по контролю за моделями искусственного интеллекта в рамках поэтапного вступления в силу закона AI Act. Теперь регулятор может требовать предоставить модель для проверки до её вывода на рынок ЕС, ограничивать доступ к евро

1😢1

3 Aug 2026, 04:37 UTC195 views4 reactionsread 7 August 2026

Суд в Москве отказался признать сгенерированные ИИ изображения творчеством Автор сгенерированных в нейросети изображений "Мона Лиза с вином" и "Статуя Свободы с вином" не смог добиться защиты авторских прав, поскольку суд в Москве посчитал их создание не творчеством, а техническим процессом, следует из материалов в распоряжении РИА Новости. Автор иска указал, что переработал в нейросети репродукции картины "Мона Ли

😱21👍1

2 Aug 2026, 17:16 UTC163 views2 reactionsread 7 August 2026
Forwarded from @hive_trace

📣 Актуальные сценарии работы HiveTrace с OpenClaw и Claude Сегодня на вебинаре показали, как с помощью HiveTrace Hooks контролировать работу Claude, рассказали о способах защиты OpenClaw и продемонстрировали атаки на агентов. ▶️ СМОТРЕТЬ 🟦 СМОТРЕТЬ Поделитесь в комментариях: какие действия AI-агентов в вашей инфраструктуре требуют особого контроля?

👍1🔥1

31 Jul 2026, 09:42 UTC203 views2 reactionsread 7 August 2026

⭐️ Запускаем четвертый поток учебной программы по AI Governance! Учитывая стремительный рост и востребованность нового направления AI Governance, Академия АйТи FabricaONE.AI (акционер - ГК Softline) с 11 по 22 августа проводит еще один поток новой корпоративной учебной программы «AI Governance в критических отраслях: от рисков и угроз к этике и доверию». Учебная программа составлена на основе самых передовых трендо

🔥2

30 Jul 2026, 12:46 UTC163 views5 reactionsread 7 August 2026

Инциденты MLSecOps. Из российских компаний утекло через ИИ-сервисы в 30 (!!!) раз больше данных, чем в прошлом году За 2025 г. в нейронные сети, такие как ChatGPT и Gemini, попало в 30 раз больше конфиденциальной информации из российских компаний, чем годом ранее. Главная причина — это массовая практика сотрудников загружать в чат-боты рабочие документы для их анализа. Ситуацию усугубляет правовой вакуум: около 60%

😱4🤗1

30 Jul 2026, 12:46 UTC175 views3 reactionsread 7 August 2026

Похожий ИТ-инцидент произошел в Samsung. Инженеры полупроводникового подразделения использовали ChatGPT для проверки и оптимизации исходного кода, а также для создания транскрипций записей совещаний. В результате фрагменты секретного исходного кода и другая конфиденциальная информация оказались на серверах OpenAI и могли быть использованы для дальнейшего обучения ИИ-модели. Компании Samsung пришлось экстренно вводить

😱3

30 Jul 2026, 12:46 UTC174 views3 reactionsread 7 August 2026

Инциденты AI Governance. Канадский депутат зачитал в парламенте речь с советом от ИИ Этот инцидент произошел в июне. Политик, судя по всему, не заметил, что скопировал готовый текст вместе с инструкцией от нейросети, и продолжил читать как ни в чем не бывало. Никто из присутствующих не остановил его. Как отмечает издание, оплошность Оливера много недель оставалась незамеченной. "Вот более естественно звучащий вариа

😱3

29 Jul 2026, 05:13 UTC217 views3 reactionsread 7 August 2026

Женщина загрузила в DeepSeek служебные документы — ее уволили за разглашение коммерческой тайны. Случай произошел в Москве, сотрудница работала в инженерной компании директором по продажам, говорится в материалах суда, которые изучило РИА Новости. При этом общением с нейросетью дело не ограничилось — женщина в том числе пересылала служебные документы на личную почту. После разглашения коммерческой тайны контрагент

😱3

Showing the 12 most recent of 20 posts we hold for @ml_ops. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 312,800 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

Names

Channels on the register whose handles appear in this channel's posts.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 11 August 2026 — this entry's latest reading, not the date you are reading this.

“MLSecOps | AI Governance | AI Reliability & Safety | IT Trends” (@ml_ops), 1,256 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/ml_ops.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.